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Question 1:
A new algorithm has been written in Python to identify SPAM e-mails. The algorithm analyzes the free text contained within a sample set of 1 million e-mails stored on Amazon S3. The algorithm must be scaled across a production dataset of
5 PB, which also resides in Amazon S3 storage.
Which AWS service strategy is best for this use case?
A. Copy the data into Amazon ElastiCache to perform text analysis on the in-memory data and export the results of the model into Amazon Machine Learning.
B. Use Amazon EMR to parallelize the text analysis tasks across the cluster using a streaming program step.
C. Use Amazon Elasticsearch Service to store the text and then use the Python Elasticsearch Client to run analysis against the text index.
D. Initiate a Python job from AWS Data Pipeline to run directly against the Amazon S3 text files.
Correct Answer: C
Reference: https://aws.amazon.com/blogs/database/indexing-metadata-in-amazon-elasticsearch-service-using-aws-lambda-and-python/
Question 2:
A data engineer chooses Amazon DynamoDB as a data store for a regulated application. This application must be submitted to regulators for review. The data engineer needs to provide a control framework that lists the security controls from
the process to follow to add new users down to the physical controls of the data center, including items like security guards and cameras.
How should this control mapping be achieved using AWS?
A. Request AWS third-party audit reports and/or the AWS quality addendum and map the AWS responsibilities to the controls that must be provided.
B. Request data center Temporary Auditor access to an AWS data center to verify the control mapping.
C. Request relevant SLAs and security guidelines for Amazon DynamoDB and define these guidelineswithin the application\’s
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